Federated Continual Learning Goes Online: Uncertainty-Aware Memory Management for Vision Tasks and Beyond
Fuente:
arXiv
Saved in:
| Main Authors: | Serra, Giuseppe, Buettner, Florian |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
How to Leverage Predictive Uncertainty Estimates for Reducing Catastrophic Forgetting in Online Continual Learning
by: Serra, Giuseppe, et al.
Published: (2024)
by: Serra, Giuseppe, et al.
Published: (2024)
DATS: Distance-Aware Temperature Scaling for Calibrated Class-Incremental Learning
by: Serra, Giuseppe, et al.
Published: (2025)
by: Serra, Giuseppe, et al.
Published: (2025)
Better Uncertainty Calibration via Proper Scores for Classification and Beyond
by: Gruber, Sebastian G., et al.
Published: (2022)
by: Gruber, Sebastian G., et al.
Published: (2022)
Beyond Overconfidence: Foundation Models Redefine Calibration in Deep Neural Networks
by: Hekler, Achim, et al.
Published: (2025)
by: Hekler, Achim, et al.
Published: (2025)
Improving Perturbation-based Explanations by Understanding the Role of Uncertainty Calibration
by: Decker, Thomas, et al.
Published: (2025)
by: Decker, Thomas, et al.
Published: (2025)
Why Uncertainty Calibration Matters for Reliable Perturbation-based Explanations
by: Decker, Thomas, et al.
Published: (2025)
by: Decker, Thomas, et al.
Published: (2025)
From Entropy to Calibrated Uncertainty: Training Language Models to Reason About Uncertainty
by: Jenane, Azza, et al.
Published: (2026)
by: Jenane, Azza, et al.
Published: (2026)
Non-Contrastive Vision-Language Learning with Predictive Embedding Alignment
by: Kuhn, Lukas, et al.
Published: (2026)
by: Kuhn, Lukas, et al.
Published: (2026)
A Bias-Variance-Covariance Decomposition of Kernel Scores for Generative Models
by: Gruber, Sebastian G., et al.
Published: (2023)
by: Gruber, Sebastian G., et al.
Published: (2023)
Mind the Gap: A Framework for Assessing Pitfalls in Multimodal Active Learning
by: Eisenhardt, Dustin, et al.
Published: (2026)
by: Eisenhardt, Dustin, et al.
Published: (2026)
Incremental Uncertainty-aware Performance Monitoring with Active Labeling Intervention
by: Koebler, Alexander, et al.
Published: (2025)
by: Koebler, Alexander, et al.
Published: (2025)
Uncertainty-Aware Federated Learning for Cyber-Resilient Microgrid Energy Management
by: Babayomi, Oluleke, et al.
Published: (2025)
by: Babayomi, Oluleke, et al.
Published: (2025)
MoRE-LLM: Mixture of Rule Experts Guided by a Large Language Model
by: Koebler, Alexander, et al.
Published: (2025)
by: Koebler, Alexander, et al.
Published: (2025)
Task-Core Memory Management and Consolidation for Long-term Continual Learning
by: Huai, Tianyu, et al.
Published: (2025)
by: Huai, Tianyu, et al.
Published: (2025)
Machine Learning based Analysis for Radiomics Features Robustness in Real-World Deployment Scenarios
by: Khan, Sarmad Ahmad, et al.
Published: (2025)
by: Khan, Sarmad Ahmad, et al.
Published: (2025)
Towards Uncertainty-Aware Federated Granger Causal Learning
by: Mohanty, Ayush, et al.
Published: (2026)
by: Mohanty, Ayush, et al.
Published: (2026)
Fine-Grained Uncertainty Decomposition in Large Language Models: A Spectral Approach
by: Walha, Nassim, et al.
Published: (2025)
by: Walha, Nassim, et al.
Published: (2025)
From Offline to Online Memory-Free and Task-Free Continual Learning via Fine-Grained Hypergradients
by: Michel, Nicolas, et al.
Published: (2025)
by: Michel, Nicolas, et al.
Published: (2025)
Contextual Online Uncertainty-Aware Preference Learning for Human Feedback
by: Lu, Nan, et al.
Published: (2025)
by: Lu, Nan, et al.
Published: (2025)
Efficient and Uncertainty-Aware Diffusion Framework for Offline-to-Online Reinforcement Learning
by: Bui, Ha Manh, et al.
Published: (2026)
by: Bui, Ha Manh, et al.
Published: (2026)
Exploiting Task Relationships in Continual Learning via Transferability-Aware Task Embeddings
by: Wu, Yanru, et al.
Published: (2025)
by: Wu, Yanru, et al.
Published: (2025)
Task-Awareness Improves LLM Generations and Uncertainty
by: Tomov, Tim, et al.
Published: (2026)
by: Tomov, Tim, et al.
Published: (2026)
Uncertainty-Aware Explainable Federated Learning
by: Zhang, Yanci, et al.
Published: (2025)
by: Zhang, Yanci, et al.
Published: (2025)
Inherently Interpretable and Uncertainty-Aware Models for Online Learning in Cyber-Security Problems
by: Kolicic, Benjamin, et al.
Published: (2024)
by: Kolicic, Benjamin, et al.
Published: (2024)
FedMeS: Personalized Federated Continual Learning Leveraging Local Memory
by: Xie, Jin, et al.
Published: (2024)
by: Xie, Jin, et al.
Published: (2024)
Distillation-Guided Structural Transfer for Continual Learning Beyond Sparse Distributed Memory
by: Xue, Huiyan, et al.
Published: (2025)
by: Xue, Huiyan, et al.
Published: (2025)
Knowledge-Aware Evolution for Streaming Federated Continual Learning with Category Overlap and without Task Identifiers
by: Tan, Sixing, et al.
Published: (2026)
by: Tan, Sixing, et al.
Published: (2026)
Efficient RF Passive Components Modeling with Bayesian Online Learning and Uncertainty Aware Sampling
by: Zhang, Huifan, et al.
Published: (2025)
by: Zhang, Huifan, et al.
Published: (2025)
Heat Kernel Goes Topological
by: Krahn, Maximilian, et al.
Published: (2025)
by: Krahn, Maximilian, et al.
Published: (2025)
Is Prompt Selection Necessary for Task-Free Online Continual Learning?
by: Park, Seoyoung, et al.
Published: (2026)
by: Park, Seoyoung, et al.
Published: (2026)
Information-Geometric Barycenters for Bayesian Federated Learning
by: Jamoussi, Nour, et al.
Published: (2024)
by: Jamoussi, Nour, et al.
Published: (2024)
Task-Agnostic Federated Continual Learning via Replay-Free Gradient Projection
by: Cha, Seohyeon, et al.
Published: (2025)
by: Cha, Seohyeon, et al.
Published: (2025)
L2XGNN: Learning to Explain Graph Neural Networks
by: Serra, Giuseppe, et al.
Published: (2022)
by: Serra, Giuseppe, et al.
Published: (2022)
Beyond Sliding Windows: Learning to Manage Memory in Non-Markovian Environments
by: Tasse, Geraud Nangue, et al.
Published: (2025)
by: Tasse, Geraud Nangue, et al.
Published: (2025)
FedHybrid: Breaking the Memory Wall of Federated Learning via Hybrid Tensor Management
by: Tam, Kahou, et al.
Published: (2025)
by: Tam, Kahou, et al.
Published: (2025)
TADPO: Reinforcement Learning Goes Off-road
by: Wu, Zhouchonghao, et al.
Published: (2026)
by: Wu, Zhouchonghao, et al.
Published: (2026)
Disentangling Mean Embeddings for Better Diagnostics of Image Generators
by: Gruber, Sebastian G., et al.
Published: (2024)
by: Gruber, Sebastian G., et al.
Published: (2024)
Decentralized Fairness Aware Multi Task Federated Learning for VR Network
by: Tharakan, Krishnendu S., et al.
Published: (2025)
by: Tharakan, Krishnendu S., et al.
Published: (2025)
Ferret: An Efficient Online Continual Learning Framework under Varying Memory Constraints
by: Zhou, Yuhao, et al.
Published: (2025)
by: Zhou, Yuhao, et al.
Published: (2025)
Network Interdiction Goes Neural
by: Zhang, Lei, et al.
Published: (2024)
by: Zhang, Lei, et al.
Published: (2024)
Similar Items
-
How to Leverage Predictive Uncertainty Estimates for Reducing Catastrophic Forgetting in Online Continual Learning
by: Serra, Giuseppe, et al.
Published: (2024) -
DATS: Distance-Aware Temperature Scaling for Calibrated Class-Incremental Learning
by: Serra, Giuseppe, et al.
Published: (2025) -
Better Uncertainty Calibration via Proper Scores for Classification and Beyond
by: Gruber, Sebastian G., et al.
Published: (2022) -
Beyond Overconfidence: Foundation Models Redefine Calibration in Deep Neural Networks
by: Hekler, Achim, et al.
Published: (2025) -
Improving Perturbation-based Explanations by Understanding the Role of Uncertainty Calibration
by: Decker, Thomas, et al.
Published: (2025)